Literature DB >> 25349725

A randomized clinical trial of nutrition education for improvement of diet quality and inflammation in Iranian obese women.

Majid Mohammadshahi1, Fatemeh Haidari2, Majid Karandish2, Sara Ebrahimi3, Mohammad-Hosein Haghighizadeh4.   

Abstract

Background. Obesity is considered as a low grade inflammation condition. The aim of this study was to investigate the effect of nutritional education on diet quality and biomarkers of inflammation in Iranian obese women. Method. Sixty obese women voluntarily participated in this randomized clinical trial and were randomly assigned to intervention or control group (n = 30). Intervention group was instructed to attend nutrition education sessions (1 hr/wk, for 3 months) in small groups. Diet quality scores were measured by Healthy Eating Index (HEI). Anthropometric indices and serum concentration of hs-CRP, TNF-α, and adiponectin were measured at the baseline and end of the intervention. Results. There were no significant differences in anthropometric indices of participants between the two groups at the end of intervention (P > 0.05). However, the total HEI score was significantly higher in the educated group compared to the control group after intervention (P < 0.05). The educated group also showed significant lower concentration of TNF-α and hs-CRP and higher levels of adiponectin than the control group at the end of study (P < 0.05). Conclusions. Our results provide limited evidence that higher dietary quality contributes to reduced inflammation in obese women. This effect could be independent of the weight loss.

Entities:  

Year:  2014        PMID: 25349725      PMCID: PMC4202200          DOI: 10.1155/2014/605782

Source DB:  PubMed          Journal:  J Nutr Metab        ISSN: 2090-0724


1. Background

The link between unhealthy eating habits and obesity is well established [1-4]. Since human diets contain many components that may work synergistically to prevent or promote disease, assessing that diet quality may be an informative strategy when studying the relation between nutrition and obesity [5-8]. Indexes of dietary quality have been developed to address this need in nutrition research. Two of these, the Healthy Eating Index (HEI) and the Diet Quality Index (DQI), were developed to measure adherence to dietary guidelines and were shown to adequately measure overall diet quality [9, 10]. The HEI measures adherence to the Food Guide Pyramid developed in the mid-1990s, whereas the DQI reflects a person's adherence to the Diet and Health recommendations of the National Academy of Sciences [11]. Obesity is a low-grade inflammatory condition; however, limited studies to date have considered the overall quality of the diet and its relation to obesity-induced inflammation; these have been mainly limited to the cross-sectional studies [1, 12, 13]. According to findings from the National Health and Nutrition Examination Survey III, the HEI score was inversely associated with C-reactive protein (CRP) concentration, which was largely attributed to total grain consumption [13]. Fung et al., however, found no association between HEI score and various markers of inflammation and endothelial dysfunction [14]. Fargnoli et al. showed that adherence to a healthier diet, as reflected by a higher HEI score, is associated with higher plasma adiponectin and lower plasma resistin, CRP, and E-selectin levels independent of obesity and lifestyle factors [2]. Thus, dietary quality may be inversely associated with inflammatory conditions independent of BMI [12]. Although concentrations of inflammatory markers and adipokines were previously associated with modifiable lifestyle factors (or dietary patterns) in cross-sectional studies, diet quality has not been previously studied in relation to proinflammatory factors and adiponectin during nutritional intervention. According to Tehran Lipid and Glucose Study (TLGS), the diet quality of most people in Tehran, Iran, (74%) needs improvement and thus nutritional education to improve diet quality is recommended [15]. The purpose of the study reported here was to evaluate if nutrition education could improve diet quality, as measured by HEI score, and thereby it would be independent of weight loss associated with improving of inflammatory markers (hs-CRP and TNF-α) and adiponectin concentration.

2. Methods

2.1. Study Setting and Design

This study was designed as a randomized clinical trial to investigate the effects of nutritional education for 3 months on the improvement of HEI scores and serum levels of inflammatory markers in obese women. At first, a call for participating in the study was provided and the aim of the study was described completely to who attended to the Health and Nutrition Clinic of Ahvaz, Iran. Then regarding the inclusion and exclusion criteria, subjects were selected. Inclusion criteria were women with body mass index (BMI) ≥30, having an initial HEI score <80, under conditions of weight stability for at least 3 months, and subject satisfaction. Exclusion criteria included chronic disease (diabetes, cardiovascular disease, cancer, arthritis, lung disease, asthma, or serious allergies), being active in exercise or weight reduction programs, taking weight loss medications, taking drugs that are known to affect the immune system, including nonsteroidal anti-inflammatory medications and corticosteroids, consumption of nutritional supplements at least 6 months before sampling, alcohol consumption, vegan diet, smoking, and lack of subject follow-up (being absent in 2 or more education sessions). We also excluded under and over reporters of energy intakes [15].

2.2. Study Population, Sample Size, and Sampling

Finally, sixty obese women, aged 20–45 y, who had volunteered, were randomly divided into two groups (education group: n = 30 and noneducation group: n = 30) using a table of random numbers with block size not revealed to the investigators. Those randomized to the intervention (education) group were instructed to attend nutrition education sessions (1 hr/wk for 3 months, 12 sessions) in small groups (6 persons per session) conducted by a registered dietitian. All subjects in this group received the same information over the course of 3 months of participation. Each 1 hr session included an oral presentation on nutrition information relevant to healthy diet and HEI recommendations. In this study, the nutrition education program was based on the modified My Plate (regarding to Iranian food culture) and food pyramid guideline. All participants in the education group were also provided with a designated booklet related to nutrition education. The control group in this study did not receive the nutrition education program and they were educated for food recording only.

2.3. Data Collection and Procedure

In this study, all participants were requested not to change their physical activity habits during the study. At baseline and the end of the study, anthropometric measurements (weight, height, waist circumference (WC), and hip circumference (HC)) were measured and then waist-to-hip ratio (WHR) was determined. Body mass index (BMI) was calculated from measured height and weight. Participants' body fat percent was also measured by body state set (Quad Scan 4000). Dietary intakes were assessed by the seven consecutive days' food record. On the basis of 7 days' food record, each HEI component score was calculated for each individual. The HEI total score was also calculated as the sum of these scores over the 12 components. Then, for each component score and for the total score, the mean score was taken. Briefly, the HEI-2005 comprises 12 components, which are scored on a scale from 0 to maximum (M), where M is 5, 10, or 20 according to the component. Thus, the composite HEI score can potentially range from a minimum of zero to a maximum score of 100, with 100 points referring to perfect diet quality and lower results indicating larger deviations from the recommended intakes [7]. For each individual and each component, the ratio of the reported intake of food group (relevant to the HEI component considered) to the reported energy intake was also calculated. Then, the mean of these ratios over the individuals was taken. All of the dietary and anthropometric data were collected by an expert registered dietitian. In this study, a modified Nutritionist IV program was used to estimate dietary intake of participants.

2.4. Biochemical Analysis

At baseline and the end of the study, fasting blood samples were also collected from all the participants, and sera were separated for biochemical analyses. Serum concentrations of hs-CRP, TNF-α, and adiponectin were measured using a commercially available enzyme-linked immunosorbent assays (ELISA) method (Labor Diagnostika Nord for hs-CRP and Orgenium laboratories-Finland for TNF-α and adiponectin). All assays were performed according to the manufacturer's instructions.

2.5. Statistical Analysis

All statistical analyses were performed with Statistical Package for Social Sciences (SPSS Inc., Chicago, IL, USA) Program version 18 for windows. At first, normal distribution of all variables was checked with the Kolmogorov-Smirnov test. Group variable means were compared with each other using both independent sample t-test and ANCOVA in the adjusted models, which were adjusted for confounders (age, weight, and energy intake). The end values of each variable were also compared with the baseline values using paired sample t-test. The differences with P values <0.05 were considered as significant.

2.6. Ethnic

The study was approved by and performed under the guidelines of the Research Ethics Committee of Ahvaz Jundishapur University of Medical Sciences, Iran (ETH-9115). A written consent was also obtained from all the participants.

3. Results

In this study, 60 participants with 34.15 ± 5.34 years old were included in the study. Sociodemographic and anthropometrics characteristics of the study participants at baseline and the end of the study are described in Table 1. There were no significant differences in baseline and end of study measures of participants (age, income, education, physical activity, weight, BMI, WC, HC, WHR, and fat percent) between the two groups. The anthropometric indices did not also decrease within groups at the end of study when compared to the baseline values.
Table 1

Sociodemographic and anthropometric characteristics of the study groups at the baseline and end of study.

VariablesEducated group (n = 30)Noneducated group (n = 30) P1 P2
Age (y)33.13 ± 5.6035.13 ± 4.970.211
Income [n (%)]0.5160.306
 Low4 (13.33)6 (19.98)
 Medium22 (73.26)19 (63.27)
 High4 (13.33)5 (16.65)
Educational level [n (%)]0.9110.783
 <6 years1 (3.33)0
 6–12 years5 (16.65)7 (23.31)
 >12 years24 (79.92)23 (76.59)
Physical activity [n (%)]0.8520.771
 Light22 (73.26)21 (69.93)
 Moderate6 (19.98)8 (26.64)
 Heavy2 (6.66)1 (3.33)
Weight (kg)
 Baseline91.1 ± 10.692.5 ± 14.60.6720.581
 End89.8 ± 12.891.8 ± 13.50.5330.671
P30.1450.348
BMI
 Baseline34.9 ± 3.934.7 ± 5.070.8770.676
 End34.3 ± 4.334.5 ± 5.110.8520.845
P30.0900.466
WC (cm)
 Baseline 107.3 ± 10.8107.6 ± 13.20.9100.721
 End106.2 ± 8.3108.2 ± 13.50.5100.511
P30.1610.416
HC (cm)
 Baseline 110.2 ± 10.4108.8 ± 10.10.5930.804
 End109.5 ± 7.6109 ± 9.90.8120.973
P30.7440.832
WHR
 Baseline0.97 ± 0.100.98 ± 0.060.6550.690
 End0.97 ± 0.090.99 ± 0.070.4170.553
P30.8020.424
Fat percent (%)
 Baseline34.6 ± 6.333.5 ± 7.20.2110.189
 End33.8 ± 6.633.4 ± 6.20.4250.385
P30.2530.837

BMI: body mass index; WC: waist circumference; HC: hip circumference; and WHR: waist to hip ratio.

Data were expressed as mean ± SD or percentages.

P1 resulted from independent sample t-test or chi-squared test as appropriate; P2 resulted from ANCONA test (adjustment for age and energy intake); and P3 resulted from paired sample t-test.

Dietary intakes of the study participants are presented in Table 2. Total carbohydrate and total fat intake of participants decreased at the end of the study compared to the educated and the noneducated groups at baseline (P < 0.05). At the end of study, dietary intakes of total fat also decreased significantly in the educated group when compared to the control group (P = 0.000). This result remained significant after adjustment for confounding variables (age and energy intake).
Table 2

Dietary intakes of the study groups at the baseline and end of study.

VariablesEducated group (n = 30)Noneducated group (n = 30) P1 P2
Energy (Kcal)
 Baseline2232 ± 5932086 ± 3200.0860.105
 End2041 ± 3151931 ± 2490.1400.246
P30.0660.073
Protein (gr)
 Baseline86.8 ± 25.884.1 ± 16.40.6320.483
 End81.4 ± 12.579.4 ± 14.20.6200.909
P30.2340.061
Protein (%)
 Baseline14.8 ± 2.316.0 ± 1.70.0910.063
 End16.0 ± 1.416.5 ± 2.10.3070.242
P30.3240.651
Carbohydrate (gr)
 Baseline260.2 ± 78.5219 ± 44.20.1160.522
 End206.7 ± 40.7196 ± 37.10.2970.103
P3 0.001 0.006
Carbohydrate (%)
 Baseline44.5 ± 6.342.0 ± 5.50.0710.132
 End40.4 ± 4.040.6 ± 5.80.2020.731
P30.0010.082
Fat (gr)
 Baseline109.4 ± 30.2101.7 ± 18.40.2400.407
 End73.3 ± 18.797 ± 15.7 0.000 0.000
P3 0.000 0.045
Fat (%)
 Baseline34.6 ± 6.333.5 ± 7.20.2010.083
 End33.8 ± 6.633.4 ± 6.20.2510.206
P30.1320.282

Data were expressed as mean ± SD.

P1 resulted from independent sample t-test; P2 resulted from ANCONA test in the adjusted models; and P3 resulted from paired sample t-test.

As shown in Table 3, the mean total HEI score was 60.58 ± 6.31 in educated group and 62.05 ± 5.7 in noneducated group at the baseline. Therefore, the group differences in baseline total HEI scores were not significant in this respect. Mean component scores were not significantly different between the two groups at the baseline. At the end of study, the total fruits, total vegetables, dark green and orange vegetables and legumes, whole grains, milk, meat and beans, saturated fats, sodium, and SoFAAS (calories from solid fats, alcoholic beverages, and added Sugars) component scores and consequently the total HEI score were significantly higher in the educated group compared to the control (P < 0.05). These results remained significant after adjustment for confounders. After 3 months of nutrition education, the mean total HEI score was also significantly increased in the educated group, compared to baseline values (83.34 ± 5.12 versus 60.58 ± 6.31, P = 0.000).
Table 3

Component score of HEI in the study groups at the baseline and end of study.

Components of HEIEducated group (n = 30)Noneducated group (n = 30) P1 P2
Total fruit
 Baseline3.10 ± 1.43.14 ± 1.090.8980.322
 End4.91 ± 0.333.78 ± 1.17 0.000 0.000
P3 0.000 0.110
Whole fruit
 Baseline4.27 ± 0.854.34 ± 1.250.7970.872
 End4.77 ± 0.694.77 ± 0.690.7340.500
P3 0.003 0.057
Total vegetables
 Baseline3.18 ± 1.143.44 ± 1.020.3540.119
 End4.68 ± 0.523.28 ± 0.98 0.000 0.000
P3 0.000 0.400
Dark green and orange vegetables and legumes
 Baseline1.53 ± 1.411.64 ± 1.270.7500.960
 End4.36 ± 0.861.64 ± 1.13 0.000 0.000
P3 0.000 0.598
Total grain
 Baseline4.92 ± 0.224.80 ± 0.350.8020.792
 End4.94 ± 0.474.93 ± 0.330.8580.702
P30.8730.532
Whole grain
 Baseline0.4 ± 0.10.13 ± 0.070.0360.021
 End3.1 ± 1.30.13 ± 0.49 0.000 0.000
P3 0.000 0.256
Milk
 Baseline0.89 ± 0.620.77 ± 0.340.3440.099
 End5.52 ± 2.230.64 ± 0.53 0.000 0.000
P3 0.000 0.242
Meat and beans
 Baseline6.44 ± 1.956.36 ± 2.310.8810.329
 End7.86 ± 2.035.9 ± 1.99 0.000 0.000
P3 0.005 0.237
Oils
 Baseline7.25 ± 1.817.60 ± 1.120.3770.429
 End 8.41 ± 2.258.32 ± 1.150.8430.754
P3 0.025 0.032
Saturated fat
 Baseline7.38 ± 1.547.31 ± 1.660.8490.544
 End8.65 ± 17.56 ± 1.41 0.001 0.000
P3 0.001 0.520
Sodium
 Baseline4.12 ± 2.765.80 ± 3.440.0400.028
 End6.97 ± 2.544.61 ± 3.15 0.002 0.024
P3 0.000 0.031
SoFAAS
 Baseline17.20 ± 2.1216.66 ± 1.970.2110.487
 End19.10 ± 1.2 517.76 ± 1.83 0.002 0.002
P3 0.000 0.051
Total score
 Baseline60.58 ± 6.3162.05 ± 5.70.3500.283
 End83.34 ± 5.1263.44 ± 7.49 0.000 0.000
P3 0.000 0.203

SoFAAS.

Calories from solid fats, alcoholic beverages, and added sugars.

Data were expressed as mean ± SD.

P1 resulted from independent sample t-test; P2 resulted from ANCONA test (adjustment for age and energy intake); and P3 resulted from paired sample t-test.

The relative intake of each HEI component to the energy intake is presented in Table 4. The average intake of total fruits, whole fruits, total vegetables, dark green and orange vegetables and legumes, total grains, whole grains, and milk per 1,000 kcal significantly increased after intervention in the educated group compared to baseline intakes (P < 0.05). Furthermore, the relative intake of oils, saturated fat, and sodium components significantly decreased in this group (P < 0.05). After intervention, the comparison between two groups also showed that the relative intake of total fruits, whole fruits, total vegetables, dark green and orange vegetables and legumes, total grain, whole grains, milk, and meet and beans per 1,000 kcal was significantly higher in the educated group. In contrast, a significantly lower relative intake of oils, saturated fat, sodium, and SoFAAS per 1,000 kcal was observed in the educated group, compared to the control group, at the end of study (P < 0.05). These differences even remained significant after adjustment for confounders.
Table 4

Component relative intake of HEI in the study groups at the baseline and end of study.

Components of HEIEducated group (n = 30)Noneducated group (n = 30) P1 P2
Total fruit (cup per 1000 kcal)
 Baseline0.53 ± 0.3000.51 ± 0.190.2460.689
 End1.53 ± 0.620.64 ± 0.24 0.000 0.000
P3 0.000 0.084
Whole fruit (cup per 1000 kcal)
 Baseline0.25 ± 0.120.18 ± 0.090.2350.315
 End0.43 ± 0.270.20 ± 0.29 0.000 0.000
P3 0.012 0.205
Total vegetables (cup per 1000 kcal)
 Baseline0.73 ± 0.330.77 ± 0.250.5650.339
 End1.31 ± 0.320.76 ± 0.36 0.000 0.000
P3 0.000 0.775
Dark green and orange vegetables and legumes (cup per 1000 kcal)
 Baseline0.12 ± 0.120.13 ± 0.100.7060.6 53
 End0.59 ± 0.300.13 ± 0.09 0.000 0.000
P3 0.000 0.998
Total grain (oz per 1000 kcal)
 Baseline5.92 ± 0.916.87 ± 0.890.5510.004
 End7.30 ± 0.72 6.61 ± 1.26 0.000 0.000
P3 0.049 0.063
Whole grain (oz per 1000 kcal)
 Baseline0.32 ± 0.070.62 ± 0.160.0000.000
 End0.85 ± 0.420.28 ± 1.04 0.000 0.000
P3 0.000 0.256
Milk (cup per 1000 kcal)
 Baseline0.11 ± 0.080.10 ± 0.040.1380.103
 End0.61 ± 0.2440.08 ± 0.06 0.000 0.000
P3 0.000 0.242
Meet and beans (oz per 1000 kcal)
 Baseline1.62 ± 0.521.66 ± 0.730.6130.591
 End1.76 ± 0.561.48 ± 0.50 0.030 0.025
P30.3180.130
Oils (gr per 1000 kcal)
 Baseline9.81 ± 4.7411.12 ± 2.420.5530.127
 End7.13 ± 2.3213.80 ± 3.75 0.000 0.000
P3 0.009 0.000
Saturated fat (% of energy)
 Baseline12.85 ± 2.1313.47 ± 2.120.2680.419
 End8.57 ± 2.0213.31 ± 1.80 0.000 0.000
P3 0.000 0.614
Sodium (gr per 1000 kcal)
 Baseline1.82 ± 1.201.64 ± 1.090.5540.356
 End1.02 ± 0.711.72 ± 0.97 0.011 0.025
P3 0.000 0.341
SoFAAS (% of energy)
 Baseline4.84 ± 1.506.72 ± 2.320.0010.013
 End5.17 ± 2.077.88 ± 1.83 0.000 0.000
P30.4320.044

Data were expressed as mean ± SD.

P1 resulted from independent sample t-test; P2 resulted from ANCONA test (adjustment for age and energy intake); and P3 resulted from paired sample t-test.

As presented in Table 5, significant differences were observed between the two groups regarding serum levels of inflammatory biomarkers at the end of intervention. Serum levels of TNF-α and hs-CRP were significantly lower in the educated group compared to the control group (P = 0.044 and P = 0.021, resp.). This significance remained even after adjustment for age, weight, and energy intake (P = 0.011 and P = 0.039, resp.). The educated group also showed significant higher adiponectin concentrations compared to the control group at the end of study (P = 0.035, in the adjusted models). Statistical analyses (within groups) also showed that the serum levels of TNF-α and hs-CRP significantly decreased and the mean concentration of adiponectin significantly increased after intervention in the educated group (P < 0.05).
Table 5

Serum levels of inflammatory markers in the study groups at the baseline and end of study.

VariablesEducated group (n = 30)Noneducated group (n = 30) P1 P2
Adiponectin
 Baseline8.52 ± 2.288.10 ± 3.740.6090.995
 End11.72 ± 4.24 7.26 ± 3.87 0.013 0.035
P3 0.027 0.330
TNF-α
 Baseline10.05 ± 4.609.86 ± 3.420.8580.809
 End7.91 ± 2.469.65 ± 3.85 0.044 0.011
P3 0.031 0.605
Hs-CRP
 Baseline7.50 ± 3.017.00 ± 3.430.5610.535
 End5.12 ± 2.17.41 ± 2.96 0.021 0.039
P3 0.019 0.271

Data were expressed as mean ± SD.

P1 resulted from independent sample t-test; P2 resulted from ANCONA test (adjustment for age, weight and energy intake); and P3 resulted from paired sample t-test.

4. Discussion

The results of this study showed that 3-month nutrition education improved diet quality, as measured by the HEI. Consequently, the improved diet quality was associated with the lower levels of hs-CRP and TNF-α and the higher levels of adiponectin in obese women (P < 0.05). This effect was independent of weight changes. The relationship of diet quality to obesity has been inconsistent, and lack of association between diet quality and anthropometric indicators of obesity has also been reported in other studies [1, 7, 16–19]. In a cross-sectional study conducted by Boynton et al., the HEI scores were modestly correlated with BMI, yet not with percent body fat in postmenopausal women. However, individuals with lower BMI or lower percent body fat had more healthful diets, as measured by the DQI [1]. One possible reason for these discrepant results is that while the DQI generally emphasizes moderation, half of the HEI score concerns meeting or exceeding the recommended amount of grains, fruits, vegetables, meat, and milk. Thus, an individual who eats more in general receives a higher HEI score, which may explain why no clear associations between HEI and body composition were observed [1, 17, 18]. Although recent studies have shown an important role for inflammation in obesity, limited studies have evaluated the association between diet quality and circulating level of inflammatory markers with respect to obesity [20]. Since human diets contain many components that may work synergistically to prevent or promote disease, assessing diet quality may be informative [6]. The results from a crossover study that was conducted in healthy women have shown that, after adjustment for age and energy intake, women with the highest adherence to the HEI had 24% higher plasma adiponectin and 41% lower plasma CRP than did women with the lowest adherence to the HEI. Inverse association between the HEI and TNF-α was also reported, but it was not significant after adjustment for body mass index [2]. Some studies have examined the contribution of major dietary patterns to markers of systemic inflammation. Lopez-Garcia et al., in a crossover study, showed that the prudent pattern that is characterized by higher intakes of fruit, vegetables, legumes, fish, poultry, and whole grains is inversely associated with plasma concentrations of CRP. Contrary to this finding, the Western pattern that is characterized by higher intakes of red and processed meats, sweets, desserts, French fries, and refined grains showed a positive relation with CRP and interleukin 6 after adjustment for confounders [21]. The prudent pattern and the Western pattern in Lopez-Garcia et al. study were relatively comparable to perfect diet quality and imperfect diet quality in the present study, respectively. In another study, median plasma adiponectin concentrations were 23% higher in women who most closely followed a Mediterranean-type diet than in low adherers [22]. Similar results were also reported by others [14, 23]. Similarly, Esposito et al., in a 2-y randomized controlled trial, reported that a Mediterranean-type diet accompanied by increased physical activity significantly increased adiponectin concentrations in obese postmenopausal women, even after accounting for the decreased body weight associated with the intervention [24]. The results of this study are consistent with those of the above studies and extend them by showing that adherence to a healthier diet, which is achieved by nutrition education in the educated group, was associated with higher adiponectin concentrations and lower hs-CRP and TNF-α levels. Several recent studies have shown that fiber, antioxidant, flavonoids, folate, vitamin C, beta carotene, selenium, magnesium, and cupper, which was found mainly in the HEI components (fruits, vegetables, legumes, and whole grains), are positively associated with improved metabolic responses and have beneficial effects on markers of inflammation [25, 26]. However, since foods are not eaten in isolation, recent studies affirmed the importance of the overall dietary pattern or dietary quality, rather than that of specific food groups or nutrients, to inflammatory markers [22]. Although, in the present study, the relation between total HEI components scores and inflammatory markers was not assessed, individuals with higher total HEI scores had significantly higher adiponectin concentration and lower hs-CRP and TNF-α level (Table 6). In this study, it was attempted to account for confounders that were likely associated with concentration of inflammatory markers or consumption of a diet. However, the potential for remaining confounders by uncontrolled covariates was possible, and the present study was also limited by the small sample size, short duration of the intervention, and the self-report of food intake. Finally, the sample used in this randomized clinical trial does not represent a random sample of the Iran population; thus future studies with larger sample size are needed to identify these determinants.
Table 6

Healthy eating index components and standards for scoring.

ComponentMaximum pointsStandard for maximum scoreStandard for minimum score of zero
Total fruit (includes 100% juice)5≥0.8 cup/1000 kcalNo fruit
Whole fruit (not juice)5≥0.4 cup/1000 kcalNo whole fruit
Total vegetables5≥1.1 cups/1000 kcalNo vegetables
Dark green and orange vegetables and legumes5≥0.4 cup/1000 kcalNo dark green or orange vegetables or legumes
Total grains5≥3.0 cups/1000 kcalNo grains
Whole grains5≥1.5 oz/1000 kcalNo whole grains
Milk10≥1.3 cups/1000 kcalNo milk
Meat and beans10≥2.5 oz/1000 kcalNo meat or beans
Oils10≥12 grams/1000 kcalNo oil
Saturated fat10≤7% of energy≥15% of energy
Sodium10≤0.7 gram/1000 kcal≥2.0 grams/1000 kcal
Calories from solid fat, alcohol, and added sugar (SoFAAS)20≤20% of energy≥50% of energy

5. Implications for Research and Practice

The results of this study support the hypothesis that beneficial effects of improved dietary quality with respect to obesity may be partially mediated by improvements in plasma concentrations of adiponectin and other biomarkers of systemic inflammation. This effect could be independent of weight loss and the other anthropometric variations. Future studies should extend these findings by investigating potential mechanisms underlying these relations and by examining whether prevention of the diabetes, atherosclerosis, and metabolic syndrome by diet quality improvements is mediated through changes in clinically important biomarkers, including adiponectin, hs-CRP, and TNF-α concentration.
  26 in total

1.  Whole-grain intake is favorably associated with metabolic risk factors for type 2 diabetes and cardiovascular disease in the Framingham Offspring Study.

Authors:  Nicola M McKeown; James B Meigs; Simin Liu; Peter W F Wilson; Paul F Jacques
Journal:  Am J Clin Nutr       Date:  2002-08       Impact factor: 7.045

2.  Diet-quality scores and plasma concentrations of markers of inflammation and endothelial dysfunction.

Authors:  Teresa T Fung; Marjorie L McCullough; P K Newby; Joann E Manson; James B Meigs; Nader Rifai; Walter C Willett; Frank B Hu
Journal:  Am J Clin Nutr       Date:  2005-07       Impact factor: 7.045

3.  Dairy consumption and circulating levels of inflammatory markers among Iranian women.

Authors:  Ahmad Esmaillzadeh; Leila Azadbakht
Journal:  Public Health Nutr       Date:  2009-12-15       Impact factor: 4.022

4.  Effect of weight loss and lifestyle changes on vascular inflammatory markers in obese women: a randomized trial.

Authors:  Katherine Esposito; Alessandro Pontillo; Carmen Di Palo; Giovanni Giugliano; Mariangela Masella; Raffaele Marfella; Dario Giugliano
Journal:  JAMA       Date:  2003-04-09       Impact factor: 56.272

5.  Associations between healthy eating patterns and immune function or inflammation in overweight or obese postmenopausal women.

Authors:  Alanna Boynton; Marian L Neuhouser; Mark H Wener; Brent Wood; Bess Sorensen; Zehava Chen-Levy; Elizabeth A Kirk; Yutaka Yasui; Kristin Lacroix; Anne McTiernan; Cornelia M Ulrich
Journal:  Am J Clin Nutr       Date:  2007-11       Impact factor: 7.045

6.  The healthy eating index and youth healthy eating index are unique, nonredundant measures of diet quality among low-income, African American adolescents.

Authors:  Kristen M Hurley; Sarah E Oberlander; Brian C Merry; Margaret M Wrobleski; Ann C Klassen; Maureen M Black
Journal:  J Nutr       Date:  2008-12-11       Impact factor: 4.798

7.  Selected nutritional biomarkers predict diet quality.

Authors:  Marian L Neuhouser; Ruth E Patterson; Irena B King; Neilann K Horner; Johanna W Lampe
Journal:  Public Health Nutr       Date:  2003-10       Impact factor: 4.022

8.  Diet quality measures and cardiovascular risk factors in France: applying the Healthy Eating Index to the SU.VI.MAX study.

Authors:  Adam Drewnowski; Elizabeth C Fiddler; Luc Dauchet; Pilar Galan; Serge Hercberg
Journal:  J Am Coll Nutr       Date:  2009-02       Impact factor: 3.169

9.  Adherence to the Mediterranean diet attenuates inflammation and coagulation process in healthy adults: The ATTICA Study.

Authors:  Christina Chrysohoou; Demosthenes B Panagiotakos; Christos Pitsavos; Undurti N Das; Christodoulos Stefanadis
Journal:  J Am Coll Cardiol       Date:  2004-07-07       Impact factor: 24.094

10.  Evaluation of dietary quality of adolescents using Healthy Eating Index.

Authors:  Nilufer Acar Tek; Hilal Yildiran; Gamze Akbulut; Saniye Bilici; Eda Koksal; Makbule Gezmen Karadag; Nevin Sanlıer
Journal:  Nutr Res Pract       Date:  2011-08-31       Impact factor: 1.926

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  6 in total

1.  Fit & Strong! Plus Trial Outcomes for Obese Older Adults with Osteoarthritis.

Authors:  Susan L Hughes; Lisa Tussing-Humphreys; Linda Schiffer; Renae Smith-Ray; David X Marquez; Andrew D DeMott; Michael L Berbaum; Marian L Fitzgibbon
Journal:  Gerontologist       Date:  2020-04-02

2.  Use of the Healthy Eating Index in Intervention Studies for Cardiometabolic Risk Conditions: A Systematic Review.

Authors:  Paula Brauer; Dawna Royall; Ariellia Rodrigues
Journal:  Adv Nutr       Date:  2021-07-30       Impact factor: 8.701

3.  Association of Healthy Eating Index and the Alternative Healthy Eating Index with the cell blood count indices.

Authors:  Maryam Saberi-Karimian; Hamideh Ghazizadeh; Marzieh Kabirian; Elham Barati; Mohammad Sobhan Sheikh Andalibi; Smaneh Khakpour; Mina Safari; Mohammad Reza Baghshani; Seyed Mostafa Parizadeh; Maryam Tayefi; Gordon A Ferns; Majid Ghayour-Mobarhan
Journal:  Acta Biomed       Date:  2021-05-12

4.  Diet Quality and Nutrient Intake of Urban Overweight and Obese Primarily African American Older Adults with Osteoarthritis.

Authors:  Sevasti Vergis; Linda Schiffer; Tiffany White; Andrew McLeod; Neda Khudeira; Andrew Demott; Marian Fitzgibbon; Susan Hughes; Lisa Tussing-Humphreys
Journal:  Nutrients       Date:  2018-04-13       Impact factor: 5.717

5.  The Effect of Nutrition Education Using MyPlate on Lipid Profiles, Glycemic Indices, and Inflammatory Markers in Diabetic Patients.

Authors:  Mehrnoosh Zakerkish; Shima Shahmoradi; Fatemeh Haidari; Seyed Mahmoud Latifi; Majid Mohammadshahi
Journal:  Clin Nutr Res       Date:  2022-07-25

6.  Comparison of Serum Levels of Vitamin D and Inflammatory Markers Between Women With Gestational Diabetes Mellitus and Healthy Pregnant Control.

Authors:  Fatemeh Haidari; Mohammad-Taha Jalali; Nahid Shahbazian; Mohammad-Hossein Haghighizadeh; Elham Azadegan
Journal:  J Family Reprod Health       Date:  2016-03
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